CNEC Student Interns and Fellows 2018 Presented to: Office of Proliferation Detection Office of Defense Nuclear Nonproliferation Research and Development, National Nuclear Security Administration Presented by: Yousry Azmy, CNEC Director North Carolina State University Bobbie-Jo Webb-Robertson Pacific Northwest National Laboratory Jeffrey Favorite Los Alamos National Laboratory David Williams Oak Ridge National Laboratory Stephan Friedrich Lawrence Livermore National Laboratory Bernadette Kirk Kirk Nuclear Information Services October 31, 2018
Transcript
CNEC Student Interns and Fellows 2018
Presented to:
Office of Proliferation Detection Office of Defense Nuclear Nonproliferation Research and Development, National Nuclear Security Administration
Presented by:
Yousry Azmy, CNEC Director North Carolina State University
Bobbie-Jo Webb-Robertson Pacific Northwest National Laboratory
Jeffrey Favorite Los Alamos National Laboratory
David Williams Oak Ridge National Laboratory
Stephan Friedrich Lawrence Livermore National Laboratory
Section IV: Fellows 2018 ..................................................................................................................... 53 Jennifer Arthur ................................................................................................................................ 54 Connor Awe ..................................................................................................................................... 56 Carl Britt ........................................................................................................................................... 58 Alex Clark ......................................................................................................................................... 60 Joseph Cope .................................................................................................................................... 62 Adam Drescher ................................................................................................................................ 64 Samuel Hedges ............................................................................................................................... 66 Dylan Hoagland ............................................................................................................................... 68 Joel Kulesza ..................................................................................................................................... 70 Scott Richards ................................................................................................................................. 72 Raffi Yessayan ................................................................................................................................. 74
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INTRODUCTION: CONSORTIUM FOR NONPROLIFERATION ENABLING CAPABILITIES (CNEC)
The Consortium for Nonproliferation Enabling Capabilities (CNEC) is a five-year, $25M project funded by the National Nuclear Security Administration’s (NNSA) Office of Defense Nuclear Nonproliferation Research and Development. CNEC was awarded in 2014 in a national competition comprising 23 teams from across the US.
CNEC’s Mission
Through an intimate mix of innovative research and development (R&D) and education activities, CNEC will enhance national capabilities in the detection and characterization of special nuclear material (SNM) and facilities processing SNM to enable the U.S. to meet its international nonproliferation goals, as well as to investigate the replacement of radiological sources so that they could not be misappropriated and used in dirty bombs or other deleterious uses
CNEC’s Vision
The CNEC vision is to be the preeminent research and education hub dedicated to the development of enabling technologies and technical talent for meeting the present and future grand challenges of nuclear nonproliferation.
CNEC’s Thrust Areas
1. Signatures and Observables (S&O): Identifying and exploiting signatures and observables associated with SNM production, storage, and movement
2. Simulation, Analysis, and Modeling (SAM): Developing simulation, analysis, and modeling methods to identify and characterize SNM and facilities processing SNM
3. Data Fusion & Analytic Techniques (DFAT): Applying multi-source data fusion and analytic techniques to detect nuclear proliferation activities
4. Replacement of Dangerous Radiological Sources (RDRS): Developing viable replacements for potentially dangerous industrial and medical radiological sources
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CNEC University and National Laboratory Participants
The North Carolina State University (NCSU) State-led team of collaborators with principal investigators (PI) is listed in the table below. Academic disciplines include nuclear engineering, electrical engineering, computer engineering, computer science, statistics, mathematics, public and international affairs. Additionally, the consortium involves undergraduate and graduate students and postdoctoral fellows in a variety of technical fields.
CNEC FACULTY and LABORATORY REPRESENTATIVES
University or National Laboratory Participant
University of Michigan (UM) Dr. William R. Martin Dr. Brian Kiedrowski
Dr. Ed Larsen
Purdue University Dr. Lefteri Tsoukalas
Dr. Miltos Alamaniotis Dr. Chan Choi
University of Illinois at Urbana-Champaign (UIUC)
Dr. Kathryn Huff Dr. Rizwan Uddin
Dr. Shiva Abbaszadeh Dr. Matthias Perdekamp
Kansas State University (KSU) Dr. William Dunn Dr. Walter McNeil
Dr. Ken Shultis
Georgia Institute of Technology (GT)
Dr. Nolan Hertel Dr. Bernard Kippelen Dr. Benjamin Klein Dr. Canek Fuentes-
Fernandez Dr. Christopher Summers
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North Carolina Agricultural and Technical State University (NCAT)
Dr. Abdellah Ahmidouch Dr. Samuel Danagoulian
North Carolina State University (NCSU)
Dr. Yousry Azmy Dr. Robin Gardner Dr. John Mattingly
Dr. Hamid Krim Dr. Alyson Wilson Dr. Ralph Smith
Dr. Eric Laber Dr. Raju Vatsavai
Dr. William Boettcher Dr. Robert Reardon
Los Alamos National Laboratory (LANL) Dr. Jeffrey Favorite
Lawrence Livermore National Laboratory Dr. Stephan Friedrich
Pacific Northwest National Laboratory (PNNL)
Dr. Robert Brigantic
Oak Ridge National Laboratory (ORNL) Dr. David Williams
SECTION I: SUMMARY OF PARTICIPANTS
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The report features the CNEC students and fellows and their activities for the year. The variety of research projects of the participants is a testament to the continued dedication of CNEC to nuclear nonproliferation goals.
For the academic year ending in the spring of 2018, CNEC had a total of 88 students and postdoctoral participants. The fields of study included computational science and engineering, computer science, international studies, electrical engineering, mechanical engineering, physics, statistics, mathematics, and nuclear Eng. The majority of participants are in the nuclear engineering field. Of the 88 participants, 25 spent the summer on research at the national laboratories.
The figures below summarize the growth in the number CNEC student and postdoctoral participants over the last three academic years.
3-Year Summary of CNEC Students and Postdoctoral Appointees by Discipline
List of CNEC and CNEC-Affiliated1 Summer Interns Summer 2018
First Name
Last Name University Academic Advisor(s)
Major Lab National Lab
Mentor
Jennifer Arthur Michigan Sara Pozzi Nuclear
Engineering LANL Rian Bahran
Kyle Beyer Michigan Brian Kiedrowski Nuclear Engineering
LANL Simon Bolding/Alex Long
Alex Clark NCSU John Mattingly Nuclear
Engineering LANL Jeff Favorite
Nate Hart NCSU Yousry Azmy Nuclear Engineering
LANL Jon Dahl
Joel Kulesza Michigan Brian Kiedrowski Nuclear Engineering.
LANL CJ Solomon
Isaac Michaud NCSU Ralph Smith/Eric
Laber Statistics LANL Brian Weaver
1 CNEC-Affiliated participants are students whose faculty advisors are funded by CNEC, but whose summer appointment is through another office of the Department of Energy (DOE).
Connor Awe Duke University Physics Dr. Phil Barbeau
Carl Britt University of Tennessee
Nuclear Engineering Dr. Jason Hayward
Alexander Clark North Carolina State
University Nuclear
Engineering Dr. John Mattingly
Joseph Samuel Cope
North Carolina State University
Nuclear Engineering Dr. Robert Hayes
Adam Drescher University of Texas Nuclear Engineering
Dr. Sheldon Landsberger
Samuel Hedges Duke University Physics Dr. Phil Barbeau
Dylan Hoagland North Carolina State University
Nuclear Engineering
Dr. Yousry Azmy
Joel Kulesza University of Michigan Nuclear
Engineering Dr. Edward Larsen
Scott Richards University of Tennessee
Nuclear Engineering Dr. Steve Skutnik
Karl Roth University of Illinois Engineering
Physics Dr. Rizwan Uddin
Raffi Yessayan North Carolina State University
Nuclear Engineering
Dr. Yousry Azmy
SECTION II: SUMMER INTERN FEEDBACK 2018
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At the end of the summer 2018 internship, the participants were asked to evaluate their experiences. The ratings below indicate the response, with 1 being least favorable or relevant and 5 being most favorable or relevant. The response is based on 17 individuals out of a total of 25 interns. All of the 17 respondents were graduate students.
Question: What were the most positive aspects of your internship?
1. Using skills from school research on an interesting research application at the lab. 2. Getting new datasets that I can work with during school year, working on cutting edge
projects. 3. I have had many opportunities to network with colleagues at other universities and
professionals in various fields. In particular, I enjoyed participating in the Keepin program because I met many graduate students in nuclear nonproliferation.
4. Being in a lab environment gave me a good perspective on what working in a national lab may be like.
5. I had exposure to real technologies and methods used in event response. I met numerous people who will serve as useful contacts for future work. The employees gave me a sense of how the labs operate and what a career here would be like.
6. The opportunity to do work tangential to my dissertation work provided me the opportunity to gain a better perspective of field that awaits me when I graduate.
4.38
4.41
4.41
4.53
4.53
4.59
4.65
4.2 4.25 4.3 4.35 4.4 4.45 4.5 4.55 4.6 4.65 4.7
A job offer from a DOE laboratory will likelydevelop from my internship experience.
The experience gave me a realistic preview of thenonproliferation field.
I was treated with the same professional level asthe other employees.
My mentor was available when needed.
My mentor explained the research project's scopeand objectives.
The work I did was challenging and stimulating.
The length of the internship was adequate.
Rating 1 lowest, 5 highest
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7. I got exposed to multiple projects and got to see different types of problems. Working with Transportation Security Administration (TSA) stakeholders on how to minimize risk at airports was a great experience!
8. Having interest in being an experimentalist, it's nice to work hands-on in a lab. 9. The most positive aspects have been how helpful and welcoming all of the lab scientists
have been. It was also great that I was exposed to three different projects. This gave me a good feel for what a full-time position at the lab would be like.
10. My internship has been wonderful in almost all regards. I was given a project to work on, but offered the flexibility to do something else if I desired. The project specifically was an excellent view into nonproliferation projects and was setup in a way for someone new to be able to pick it up without spending months learning tools. The group, and in general, the staff at PNNL has been extremely approachable and passionate about their work.
11. Getting to do hands-on work. 12. It was insightful. 13. Hands on work, access to multi-lab partnership working groups.
Question: How could your internship have been of more value to you?
1. Just being longer in general, maybe doing a school year internship could result in more productivity.
2. Seeing the training methods for rad workers would be useful for planning future projects and understanding what kind of person work should be tailored to.
3. I am not sure that it could have been more valuable. 4. If it was longer, 3 months passed by so fast! 5. It really couldn't have been more value to me. 6. Longer, more funding. 7. If nearby accommodation was made affordable for interns. 8. Clearer project scope, more clarity in structural leadership, summer housing assistance.
SECTION III: SUMMER INTERNS 2018
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Rita Appiah
Project Title
Computational Framework to Reduce False Alarm Rate in Networked Radiation Detection Devices
Project Objective
Develop improved computational algorithms to reduce false alarms in the detection of Special Nuclear Materials (SNM).
Project Description
The objective of this research is the precise and quick detection of a SNM placed inside a building or in an urban area. We use a network of detectors to detect the emitted neutrons and photons, and data analysis to classify and distinguish potentially dangerous materials from non-hazardous materials. For that purpose we use D3S Kromek (CsI) sensors and 2”x4”x16” (NaI) sensors to collect data. As more sensors are deployed some may give false alarms if the calibration is incorrect. Background radiation such as K-40 line and Tl-208 can be used to update the calibration of such detectors. This research describes the techniques we developed for characterizing these lines quickly and accurately even with rapid temperature changes in the smallest detectors.
Project Relevance to Nuclear Nonproliferation
This project seeks to enhance nuclear and radiological threat detection as a means of combating nuclear terrorism, by exploring the capabilities of a network of ubiquitous nuclear sensors to detect, locate classify and identify hidden nuclear and radiological sources.
University: North Carolina A&T State University
Advisor: Professor Abdellah Ahmidouch
Lab Mentor: Simon Labov, PhD
Global Security Division
Radiation Detection Group, LLNL
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Developed a Python Spectral Simulation framework
As a result of the statistical nature of the detection process we began simulating a synthetic data that approximates the background potassium - 40 (K-40) line at 1460 keV as measured by the LLNL D3S detector using a Poisson distribution. Also I added some continuum with a slope and included a straight line that ends at 2614 keV (0 counts at 2614 keV) and has a slope such that the initial counts in my peak gave a Peak To Total Ratio (PTT) = 0.1. A curve fit to the Poisson distribution was done using the Gaussian distribution of a scintillating detector response function which served as an approximation to the peak of interest. Increasing PTT makes the peak we wish to determine more prominent relative to background noise, as such several simulations were done to verify that increasing Total Counts (TC) reduces the Poisson noise relative to the number of counts in each channel. Spectral centroid was also determined using the center of mass method and the weighted center of mass method and compared with the expected peak position. The accuracy (bias) and precision (random error) of the solution was estimated for various iterations. Simulation of Spectral Centroid with varying TC & PTT was performed and verified that the Weighted Center of Mass Method approached the expected peak position as the PTT reduces with increasing Total Counts.
Simulated Spectra with Gain Shifts
In order to mitigate false detections for optimum results in gamma-ray spectroscopy, it is of paramount interest to ensure that all detector pulses experience a constant level of amplification (gain). Factors such as variation in temperature or voltage instabilities can introduce gain drifts into the pulse processing system.
The gain shift spectra simulation was implemented in Python for the synthetic potassium - 40 (K-40) peak.
Gain shift positions were simulated for several iterations of TC and PTT ratios.
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Kyle Beyer
Project Title
Analog Monte Carlo Thermal Radiation Transport
Project Objective
Create an analog Monte Carlo code for thermal radiation transport as an alternative to implicit
Monte Carlo. The goal is to create a high-fidelity code that avoids linearization and is useful for code-to-code verification.
Project Description
Thermal radiation transfer is the dominant mode of heat transfer in very hot systems (e.g. inertial confinement fusion experiments, stellar interiors, etc.). It is a highly nonlinear problem, where photon phase space is tightly coupled to material temperature. It is typically solved with implicit Monte Carlo, which linearizes the thermal radiation temperature equations in T4 and freezes material properties over a time step, and uses some time differencing scheme to advance discretely in time. When full sampling from the Compton scattering kernel is implemented in this method, the solution becomes stiff and unstable for all but intractably small time steps.
The goal of this project is to develop an entirely analog alternative that avoids linearization and time differencing, which is essentially a kinetic Monte Carlo method. This method samples each event (absorption, emission, scattering) from their respective rates. The method advances
University: University of Michigan
Advisor: Brian Kiedrowski
Lab Mentor: Alex Long and Simon Bolding
Computational Physics Division
Monte Carlo Methods, Codes, and Applications Group, LANL
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photon phase space and material properties, and steps forward in time, on an event-by-event basis.
Project Relevance to Nuclear Nonproliferation
While applied to thermal radiation transfer for this summer project, the development of the event-by-event Monte Carlo models has potential application in simulating non-linear responses in radiation detectors, which is directly relevant to nuclear nonproliferation. The software infrastructure used in this project is broadly relevant to other particle transport codes as well.
Products and Outcomes of Project
MARTy (Monte Carlo Analog Radiation Transport): A user-friendly, extendable modern code to investigate advanced topics in analog thermal radiation transport. MARTy is used for code-to-code verification in simple test problems. This code base may be used for other types of non-linear transport problems.
Publications and Reports
K. A. BEYER et al, “Analog Monte Carlo thermal radiation transport as an alternative to implicit Monte Carlo,” Trans. Am. Nucl. Soc., (2019) [in preparation].
Presentations
K. A. BEYER et al, “Analog Monte Carlo thermal radiation transport as an alternative to implicit Monte Carlo,” Computational Physics Student Summer Workshop, Los Alamos National Laboratory (2018).
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Joseph Cope
Project Title
Environmental Continuous Air Monitor (ECAM) Verification and Natural Beta Background Characterization
Project Objective
Evaluate methodologies related to ECAM data analysis in support of radiological emergency response missions.
Project Description
The ECAM is of interest to the Federal Radiological Monitoring and Assessment Center (FRMAC) in support of radiological emergency response missions. The need for deployed airborne monitoring for on-going releases was demonstrated during the responses to Fukushima and the LANL Forest Fire in 2011. Pre-deployment of these assets could provide enhanced analysis and protection in support of major public events and NASA radiological power supply launches. Regarding the NASA launches, Pu-238 is of primary concern. The ECAM has previously shown promise in serving as an early warning device for airborne alpha/beta contamination at levels well below the EPA’s Protective Action Guidelines.
While post-event sampling is often accomplished using portable air samplers analyzed retrospectively, continuous air monitors can provide near real-time detection on sequential sample intervals. Robust processing of the spectral energy data across highly diverse background radiation environments is paramount. Correct compensation for natural radon and thoron progeny, including alpha and beta signals, is integral for determining counts in the transuranic regions-of-interest which provide inputs to integrated air concentrations and projected dose rates. Through review and documentation of the quantities computed in the ECAM Data Analysis Program (eDAP), assessment scientists are enabled to confidently interpret and assess the incident, as well as provide feedback on additional quantities of interest.
University: North Carolina State University
Advisor: Robert Hayes
Lab Mentor: Bill Beal
Consequence Management Program, in support of DOE NNSA’s NA-84 Office of Nuclear Incident Response
Remote Sensing Laboratory – Andrews, operated by MSTS
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Project Relevance to Nuclear Nonproliferation
Canberra’s Alpha Beta ECAMs could be deployed during an ongoing release of radioactivity enabling DOE/NNSA to continually monitor airborne contamination. The ECAM, with remote data transmission, is ideal for airborne radioactivity measurements during plume passage and as an early warning device for potential radioisotope health concerns relevant to EPA’s Protective Action Guidelines.
Products and Outcomes of Project
In addition to a thorough review of calculation methodologies in the ECAM Data Analysis Program (eDAP), specific effort focused on correlation of naturally occurring alpha radiation signals to predict the beta background activity. In support of Consequence Management missions, estimation of the natural beta background would enhance discrimination of beta sources from natural background fluctuations as an early warning device for scientists and decision makers.
Presentations
SJ Cope, “ECAM eDAP Calculation Methodologies and Natural Beta Background Correlations,” Consequence Management VTC for DOE NNSA’s NA-84 Office of Nuclear Incident Response, August 15, 2018.
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Sally Ghanem
Project Title
Information Subspace-Based Fusion for Vehicle Classification
Project Objective
The objective of this work is to devise a multi-modal approach to vehicle classification and identification using an ensemble of sensors consisting of a magnetometer, microphone, and camera. We consider a more realistic unsupervised learning scenario, where no training dataset is provided and adopt a data driven approach to determine vehicle signatures utilizing key features extracted from each sensor modality. We subsequently combine the features from each sensor modality to generate a desirable universal feature and increase the classification rate of specific vehicle classes. In this work, the Robust Subspace Recovery (RoSuRe) algorithm, is exploited to integrate multiple data sources and unfold the union of subspaces structure present in each data source (sensor modality). The effectiveness of our method is evaluated by experiments on passive audio and magnetic observations along with visual features collected on vehicles. Our goal is to produce more consistent, accurate, and useful information than that provided by any individual data source.
Project Description
Union of Subspaces (UoS) is a new paradigm for signal modeling and processing, which can identify more complex trends in data sets than simple linear models. Relying on a bi-sparsity pursuit framework and advanced non-smooth optimization techniques, the Robust Subspace Recovery (RoSuRe) algorithm was introduced in the recent literature as a reliable and numerically efficient algorithm to unfold unions of subspaces. The UoS structure is unveiled by pursuing sparse self-representation of the given data. We employ the bi-sparsity framework to recover the underlying subspace structure in each sensor modality and obtain a finer level of classification by combining them. We also use the resulting UoS structure to classify new observed data points to illustrate the generalization power of our technique. A roadside sensor system was exploited to collect data from passing vehicles using various sensors, including a
University: North Carolina State University
Advisor: Hamid Krim
Lab Mentor: Ryan A. Kerekes
RF, Communications, and Cyber-Physical Security Group
Electrical and Electronics Systems Research Division, ORNL
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camera, microphone, laser range-finder, magnetometer, and low frequency RF antenna. In this study, we are using the signatures captured using passive magnetic and acoustic sensors in addition to visual features from the camera. Experiments on real data are presented to demonstrate the effectiveness of our method in solving the problem of subspace fusion with sparsely corrupted unlabeled data. We also show that the use of multiple sensing methods enhances the performance and offers more flexibility.
Project Relevance to Nuclear Nonproliferation
Developing multi-modality sensor fusion techniques is very crucial to enabling a robust detection of compliance/noncompliance with nuclear non-proliferation commitment. Data sources are typically multimodal and may include multiple types of sensor data, still images, video, and hyper-spectral imagery, satellite data, output of models and simulations, unstructured text, and internet traffic. In Nuclear Nonproliferation setting, we are also likely to have space/air borne data (images, multi-spectral), ground measurements. The main goal is to coherently fuse the heterogeneous sources of information to smartly and comprehensively answer questions about pursuing of unauthorized nuclear activity and to support the decision making.
Products and Outcomes of Project
We implemented a software package (in Matlab) to read the data collected from an ensemble of sensors and to extract discriminative features from each sensor modality. Moreover, we employ the RoSuRe algorithm to recover the underlying subspace structure in each sensor modality and combine those structures afterwards.
Publications and Reports
• R. A. Kerekes, T. P. Karnowski, M. Kuhn, M. R. Moore, B. Stinson, R. Tokola, A. Anderson and J. M. Vann, “Vehicle Classification and Identification Using Multi-Modal Sensing and Signal Learning,”, IEEE 85th Vehicular Technology Conference, Sydney, Australia, (2017).
• S. Ghanem, A. Panahi, H. Krim, R. A. Kerekes and J. Mattingly, “Information Subspace-Based Fusion for Vehicle Classification.” 26th European Signal Processing Conference (EUSIPCO), (2018).
• J. Ploetner and M. M. Trivedi, “A Multimodal Approach for Dynamic Event Capture of Vehicles and Pedestrians”, Proceedings of the 4th ACM international workshop on Video surveillance and sensor networks, pp. 203-210. ACM, (2006).
• X. Bian, A. Panahi, and H. Krim. “Bi-Sparsity Pursuit: A Paradigm for Robust Subspace Recovery.” In Elsevier Journal of Signal Processing (Revised), (2017).
• M. Elad, M. Figueiredo, and Y. Ma. “On the role of sparse and redundant representations in image processing.” Proceedings of the IEEE 98, no. 6, 972-982, (2010).
• S. Roheda, H. Krim, Z. Q. Luo and T. Wu, “Decision Level Fusion: An Event Driven Approach.” 26th European Signal Processing Conference (EUSIPCO), (2018).
• L. A. Klein, M. Mills, and D. Gibson, “Traffic detector handbook,” Federal Highway Administration, Tech. Rep., (2006).
NINESIM: Develop the Nuclear Inspection Node Event SIMulator (NINESIM) tool to provide DNDO with graphical detectability & operational cost analysis of special nuclear material (SNM) movement through an arbitrary Global Nuclear Detection Architecture (GNDA) node.
ARAM: Design, develop, and implement an operational risk-based, intel-driven decision platform to assess and quantify terrorism risk at airports. This information will be used to improve the way limited security countermeasures representing federal and state/local agencies and associated resources are deployed at an airport in order to minimize risk across the system.
Project Descriptions
NINESIM: The NINESIM project consists of the following elements: GUI & Visualization, Event Generation Module, Human Intervention Module, Background & Clutter Module, Radiation Transport Module, and System Testing. PNNL’s primary focus is the development of the Human Intervention Module (HIM). The objective HIM is to develop and implement a method that determines intervention outcomes based on human action/counteraction decisions at the simulated GNDA node. A typical Concepts of Operations (CONOPS) that is used in HIM is provided in Figure 1.
University: North Carolina State
Advisor: Dr. Eric Laber
Lab Mentors: Angela Waterworth and Robert Brigantic
Computing and Analytics Division
Applied Statistics and Computational Modeling Group, PNNL
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ARAM: Using the Department of Homeland Security risk assessment methodology we define a risk metric based on three core components: Consequence, Vulnerability and Threat. Using airport data and subject matter experts we calculate hourly baseline risk scores across all areas of an airport. Then using mathematical optimization methods ARAM assigns airport countermeasures daily schedules with the objective of minimizing total risk across the airport.
Projects Relevance to Nuclear Nonproliferation
NINESIM: Efficient and accurate modeling of GNDA nodes will improve the understanding of the SNM detection capabilities at border crossings. This in turn will lead to improved screening strategies and higher detection rates while controlling for general economic impact.
ARAM: General efficiency improvements to airport security will reduce the risk terrorist threats, but at a larger scale the successful implementation of the risk assessment model in the airport setting can lead to wider spread adoption to other transportation hubs. Moreover, the underlying methods for risk quantification, to include the quantification of deterrence, are extensible to other domains to include nuclear nonproliferation.
Products and Outcomes of Projects
NINESIM: Develop a high-fidelity, faster-than-real-time scenario processing and interpolation algorithm for simulation of GNDA nodes at border crossings. Build databases and related parameterizations of scaling functions that improve with phase-space augmentation and are anchored by measured data. Through simulation experiments provide interpretations of the all model features and their effects on detections rates.
ARAM: Will deliver a risk-based resource allocation methodology for airport security. Develop a multi-level user interface tool for managers and security personnel to use in real time. Provide the security stakeholders of Seattle–Tacoma International Airport a demonstration of the tool that will be available to users via a web accessible interface.
Publications and Reports • NINESIM: A report that summarizes the NINESIM work and design of experiments
outcomes will be delivered to the project sponsor – Countering Weapons of Mass Destruction (CWMD) Office.
• ARAM: A journal article based on the airport risk formulation and schedule optimization methodology is in progress with the hopes of publication in the Society for Risk Analysis journal.
Presentations • NINESIM: The Human Intervention Module (HIM) for the Nuclear Inspection Node Event
SIMulator (NINESIM) which was presented at the 2018 annual Military Operations Research Society (MORS) Symposium at the Naval Postgraduate School at Monterey, CA in June 2018.
• ARAM: The ARAM user interface and functionality was presented to the security stakeholders of Seattle–Tacoma International Airport (Sea-Tac).
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Evan Gonzales
Project Title
Applying New Variance Reduction Methods in Shift
Project Objective
Develop and implement new hybrid splitting/rouletting methods to increase the solution accuracy of Shift, a Monte Carlo (MC) particle transport code under development at Oak Ridge National Laboratory.
Project Description
Implementation of hybrid deterministic/Monte Carlo transport methods, such as CADIS and FW-CADIS, into existing MC codes has been shown to greatly decrease the computational cost of achieving desirable statistical uncertainties with MC transport methods. Hybrid methods typically utilize a discrete ordinates deterministic solver to generate importance meshes over a simulation’s spatial and energy domains. These importance meshes, or “weight windows”, can then be used to refine more traditional MC variance reduction methods, such as splitting and rouletting of particles.
Upon various particle history events, an individual particle can either be “split” (copies of the particle are introduced to the simulation) or “rouletted” (the particle history is terminated) by generating a random number and comparing it to the weight window’s upper and lower bounds. However, the optimal particle history event upon which splitting/rouletting should occur is often unclear.
This project involved implementing new weight window splitting/rouletting methods into Shift for various combinations of particle history events. These events include collisions (before and after scattering the particle), surface crossings, traversing a mean free path, and crossing a weight window mesh element boundary. Each of the splitting/rouletting methods were then run
University: University of Michigan
Advisor: Brian C Kiedrowski
Lab Mentor: Gregory G Davidson
Reactor and Nuclear Systems Division
Radiation Transport Group, ORNL
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over a suite of test problem models (small PWR core, dry cask, urban/city model) to be compared and analyzed in terms of solution accuracy and computation time.
Project Relevance to Nuclear Nonproliferation
Implementing variance reduction methods into codes like Shift increases their solution accuracy while maintaining a reasonable computation time. Variance reduction methods can therefore fulfill the need for high-fidelity and computationally-efficient simulations, which are in high demand for the nuclear nonproliferation community.
Products and Outcomes of Project
A total of four new weight window variance reduction options were implemented into Shift. The optimum method will likely be determined on a per problem basis and depend on the typical value of a mean free path, number of surfaces, and coarsness of the weight window mesh. Having a variety of variance reduction methods available will allow Shift users to tune the computational efficiency of their simulations.
Publications and Reports
• E. S. GONZALEZ, “Applying New Variance Reduction Methods in Shift,” Oak Ridge National Laboratory, 113328 (August 6, 2018).
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Nate Hart
Project Title
Finding High-Order Eigenpairs of the Alpha-Eigenvalue Problem in PARTISN Using ForTrilinos
Project Objective
Link PARTISN with the ForTrilinos/Trilinos library to implement the Generalized Davidson linear method and find high-order eigenpairs of the alpha-eigenvalue problem.
Project Description
The alpha-eigenvalue problem for the neutron transport equation describes the steady-state time-rate-of-change behavior of the neutron population for a given configuration. Typically, transport codes will only solve for the lowest-order alpha-eigenvalue and associated eigenfunction, as this describes the dominant behavior. However, potentially important information can be gathered from the higher-order alpha-eigenpairs that are usually truncated.
PARTISN is a discrete ordinates neutron transport code developed at Los Alamos National Laboratory that currently calculates the alpha-eigenvalue using fixed-point iterations. However, this method only finds the dominant eigenpair, so we choose to use the Generalized Davidson linear method, which has been shown to be robust in its ability to calculate higher-order eigenpairs, which are often negative and complex. To this end, the ForTrilinos Fortran interface to the Trilinos solver library is linked to PARTISN to utilize its Generalized Davidson solver.
This project incorporates high performance computing, numerical methods, and computational neutron transport to enhance the understanding of the time-rate-of-change of neutrons in a multiplying system. This research could help increase understanding of the complexities of particle distributions in systems that go from subcritical to critical and supercritical as well.
University: NC State University
Advisor: Yousry Azmy
Lab Mentor: Jon Dahl
CCS-2 (Computational Physics and Methods)
PARTISN Team, LANL
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Project Relevance to Nuclear Nonproliferation
Multiplying systems are central to nuclear nonproliferation. Being able to accurately model the subtleties of the behavior of the particle distribution in a multiplying system could allow superior evaluation of data when assessing the presence of multiplying material.
Products and Outcomes of Project
PARTISN is expected to be released with the Generalized Davidson alpha-eigenvalue solver, as it is a requested feature by its users. An in-house study of the higher-order eigenpairs will continue beyond the summer and will likely blossom into an ANS transaction or journal article. Preliminary results have already shown that the higher-order eigenpairs are sensitive to discretization parameters and the criticality of the system, but a more rigorous testing that utilizes the full capabilities of PARTISN is required.
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Aaron Hellinger
Project Title
Isomeric Decay in Actinides
Project Objective
Use a custom made high efficiency quadrupole mass separator to selective trap multiply charged ions, formed from the alpha decay of actinides, in a linear Paul trap and study their isomeric decay properties.
Project Description
We will use various actinide electroplated sources as the origin of our nuclear isomers. The source undergoes alpha decay and eject the recoil ion into a recoil gas stopper. The ions are guided with electric fields to the exit of the gas stopper with RF and DC electric fields. The ions exit a hole in the end plate and are entrained in the support gas which injects the ions into a Radio-Frequency Quadrupole (RFQ) ion guide. The ion beam will then enter a quadrupole mass separator (QMS) region. The QMS region will only transmit ions of a specific mass and charge (which can be manipulated by changing the applied DC high voltages) while the off resonant ions will be rejected and directed into the surrounding wall. The next stage after the QMS is another RFQ ion guide to focus the beam into the linear Paul trap. The linear Paul trap trap any ion that enters it. We are then able to study a specific isomeric nucleus in a low background environment.
During the project, I will have worked on and learned about modern vacuum pressure chambers and best practices, surface mount soldering, isomeric states of specific actinides, radio-frequency quadrupole ion guides and quadrupole mass separators, discrete electronics, C/C++ programming, ROOT analysis software package, ion traps, atomic and nuclear spectroscopy.
University: Kansas State University
Advisor: Dr. Bill Dunn and Dr. Walter McNeil
Lab Mentor: Dr. Jason Burke
Physical and Life Sciences Division
Nuclear and Chemical Sciences, LLNL
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Project Relevance to Nuclear Nonproliferation
Nuclear isomers and their decay properties are of wide interest in the field of Nuclear Nonproliferation. Their decay properties (fission, beta particle emission, gamma ray emission) are all used in the field for monitoring nuclear material. Nuclear spectroscopy and mass separation techniques are used to assay materials to determine their origins.
Products and Outcomes of Project
We will have created a high efficiency ion mass separator and studied the decay properties of a few actinide isomers.
Evaluate performance of an HPGe detector to ensure viability in a space application.
Project Description
LLNL researchers are developing an HPGe detector for use in investigating the composition of the asteroid 16-Psyche, which is located in the asteroid belt. A working prototype detector has been developed, but requires further evaluation to ensure functionality in space. Summer 2018 work consisted of evaluating the prototype’s mechanical, spectral, and thermal performance.
Mechanical testing was conducted to ensure the prototype remains functional after rocket launch. The system was subjected to a 3-axis vibration test, with random and sinusoidal loads. The detector was then successfully operated to prove functionality.
Spectral analysis involved determining system settings that minimized electronic noise and provided the best resolution. The detector was operated at multiple temperatures, shaping times and voltages, and the corresponding efficiencies and resolutions were documented.
Thermal performance was analyzed by documenting detector cool down time and required cooler power. Environmental heat input into the system was estimated by thermal models, cooler power, etc.
University: Kansas State University
Advisor: Dr. Walter McNeil
Lab Mentor: Dr. Morgan Burks
LLNL
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Project Relevance to Nuclear Nonproliferation
Radiation detection is critical to monitoring the presence, movement, and use of nuclear materials. Techniques used to develop the HPGe detector for this project advance radiation detection capabilities in both space and terrestrial applications.
Products and Outcomes of Project
Mechanical, spectral, and thermal performance of a prototype HPGe detector was evaluated. The characterization process is ongoing, and the launch of the final detector is scheduled for 2022.
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Jacob Inman
Project Title
Plastic scintillators stable for operating in wide ranges of humidity and temperature variations
Project Objective
To explore techniques that can serve to prolong the homogeneity and high optical transparency of scintillating plastics during extended deployment in unforgiving environments.
Project Description
The development of field-deployable radiation detection systems relies on the detection material’s resilience to harsh environmental conditions over the duration of their deployment. Plastic scintillators exposed to large temperature and humidity (T/H) fluctuations often begin to fog (via the absorption of condensed water molecules in a humid environment) or scatter light excessively (due to atomic motion increasing the probability of light refraction under large temperature changes), potentially reducing the overall lifetime of the system.
A variety of common polyvinyltoluene- and polystyrene-based scintillators were exposed to 100% relative humidity until reaching their saturation weight, at which point defect growth could be analyzed under a microscope and degradation in their scintillation light output could be measured. T/H cycling results indicate that better controlling the rate of temperature change could make damage more recoverable, and that humidity changes seem to have little effect on plastics utilizing non-aromatic cross-linked polymer chains containing large amounts of oxygen.
While the inclusion of non-aromatic compounds is undesirable due to the inevitable degradation in light output as a result (ca. 10-20% in most cases), the inclusion of a small amount of oxygen-containing bismuth neodecanoate (Bi(nd)3) unexpectedly prevented fogging while also maintaining high light output. This natural resistance to water uptake, combined with the known
University: Georgia Tech
Advisor: Dr. Nolan Hertel
Lab Mentor: Dr. Natalia Zaitseva
Physical and Life Sciences Directorate
Materials Science Division, LLNL
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gamma-sensitivity improvements Bi compounds provide even at low concentrations, suggests that such compounds could be of interest for deployment in extreme environments.
Project Relevance to Nuclear Nonproliferation
The applications for plastic scintillators in nonproliferation field scenarios are numerous. Notably, portal monitoring research and the development of radiation sensor network technology are applications well-suited to plastic scintillators while also requiring the system maintain high levels of sensitivity to radiation over long periods of time.
Products and Outcomes of Project
In anticipation of eventual field deployment, the effects of temperature and humidity on plastic scintillators was studied. While non-aromatic or oxygenated samples are resistant to these damage types, scintillator performance suffers as a result for traditional plastics, but more exotic Bi-loaded plastics did not experience degradation under the same conditions.
Publications and Reports
N.P. ZAITSEVA et al., “Plastic Scintillators Stable for Operating in Wide Ranges of Humidity and Temperature Variations,” Nucl. Instrum. Methods Phys. Res. A, (forthcoming, 2018).
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Lydia Lagari
Project I Title
ARAM (Airport Risk Assessment Model)
Project Description
The Airport Risk Assessment Model (ARAM) was designed to assist aviation security administrators and their personnel quantify national security risk. ARAM also assesses the effectiveness of different security countermeasures in order to be able to optimally deploy the countermeasures and minimize risk over time. The final goal is that ARAM will recommend the optimal daily schedules for airport countermeasures to be deployed by law enforcement and security resources that minimizes the total risk across the airport.
Project Relevance to Nuclear Nonproliferation
The relevance to nuclear nonproliferation that this project provides is learning about how to quantify risk, characterize potential adversary threats, working with subject matter experts to score risk components and countermeasure effectiveness, and to put together all of these aspects into an integrated model. Even though a different domain than nuclear nonproliferation, the methods can be extended to this domain and a similar modeling construct can be developed.
Products and Outcomes of Project
Learned about risk analysis and different ways to counter potential threats. Enriched the optimization background underlying the model. Gained experience in working directly with U.S. federal government stakeholders such as officials from the Transportation Security Administration (TSA). A paper with the outcomes of this work is in progress, and will be submitted to the international journal of the Society for Risk Analysis.
University: Purdue University
Advisor: Lefteri H. Tsoukalas
Lab Mentor: Robert Brigantic
Computing and Analytics Division
Applied Statistics and Computational Modeling Group, PNNL
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Project II Title
NINESIM (Nuclear Inspection Node Event Simulator
Project Description
NINESIM is a project developed by three teams: Los Alamos National Laboratory (LANL), Naval Research Laboratory (NRL), and Pacific Northwest National Laboratory (PNNL), with LANL being the overall project lead. It simulates a real time analysis of radiological/nuclear detection systems at port-of-entries. It builds on existing capabilities and databases, including graphics, discrete-event processing, backgrounds, and SNM radiation transport and detection aviation security. PNNL’s primary focus is the development of the Human Intervention Module (HIM). The objective HIM is to develop and implement a method that determines intervention outcomes based on human action/counteraction decisions at the simulated port-of-entry node.
Project Relevance to Nuclear Nonproliferation
This project is directly relevant to nuclear nonproliferation as NINESIM allows to ascertain the effectiveness of different radiological/nuclear detection systems and modes of operation to detect and prevent the movement of illicit radiological/nuclear materials across our borders.
Products and Outcomes of Project
Learned about Design of Experiments (DoE) and how to apply it to ascertain the performance of radiological/nuclear detection systems across a vast array of input parameters. We were able to characterize the performance of different detectors, different SNM materials, and shielding to identify capabilities and limitations of these systems. Provided subject matter expertise pertaining to SNM and radioactive materials, shielding, and detector capabilities.
Publications and Reports • P.L. LAGARI, S. WEIDENBENNER, M. ALAMANIOTIS, C. CHOI, L. TSOUKALAS. “Testing
the sensitivity of a neural based identification Algorithm to Shielding Levels,” Philadelphia PA, Transactions of the American Nuclear Society, Vol. 118: 779-782 (2018).
• An article based on the airport risk formulation and schedule optimization methodology is in progress with the hopes of publication in the Society for Risk Analysis journal.
Presentations • “An RBF Neural Network approach in radionuclide identification of unknown sources
utilizing gamma-ray spectra”. Flash Talk presented at the PNNL Faculty Summit “Deep learning for Scientific Discovery” 2018Richland WA, USA (2018).
• The ARAM user interface and functionality was presented to the security stakeholders of Seattle–Tacoma International Airport (Sea-Tac).
• Airport Risk Assessment Model (ARAM) Risk Formulation was presented at the 2018 annual Military Operations Research Society (MORS) Symposium at the Naval Postgraduate School at Monterey, CA in June 2018
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Erik Medhurst
Project Title
Holographic Visual Sample Plan (HoloVSP)
Project Objective
Reduce the complexity of collecting data for making statistical analyses with Visual Sample Plan software.
Project Description
Visual Sample Plan (VSP) is a software used to plan sample collection and make statistical decisions based on the collected data. When a user wants to make judgment on a room or environment, they will first draw it in VSP. VSP then generates random sample locations throughout the room on any surface. A user will then take the sample map and measure the distances to samples around the room and collect data at each location.
This project involves applying Augmented Reality (AR) via the Microsoft HoloLens to facilitate the sample collection process. The HoloVSP application guides users through sample plan generation on the fly. A person walks through an area and scans the surfaces to add them as potential sample locations and chooses how many random samples should be generated, and HoloVSP creates holograms of sample locations on the environment.
Holograms serve as a visual representation of where samples should be taken as well as interactable objects for tracking collection progress. Holographic samples can be marked completed or skipped and can be added or removed. The final sample plan results can be exported as a 3D model to preserve a record of locations where samples were taken.
University: University of Illinois Urbana-Champaign
Advisor: Dr. Rizwan Uddin
Lab Mentor: Nick Cramer
Computing & Analytics Division
Visual Analytics Group, PNNL
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Project Relevance to Nuclear Nonproliferation
The VSP software could be applied after radiation terrorist events to determine if a location is unsafe. The AR approach cuts the response time down so first responders can immediately enter a site and generate a sample plan in unknown prior conditions. Responders can clearly track their progress, and the results can be easily interpreted.
Products and Outcomes of Project
We developed an application that makes the slow, difficult, and inflexible sample collection process quick, easy, and adaptive. Instruction and guidance provided in the HoloVSP application potentially reduces errors in sampling. We have demonstrated this new approach for response to possible radiation terrorist events that can be implemented at any site with a fraction of the time and cost required in the current approach.
Figure 2: Screenshot of HoloVSP running on Microsoft HoloLens. Green indicates a collected sample, red indicates a sample marked to be skipped, and white indicates a sample that hasn’t been interacted with.
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Isaac Michaud
Project Title
Improved Nonparametric Mutual Information Estimation for Experimental Design
Project Objective
Improve and validate k-nearest neighbor mutual information estimators for use in optimal experimental design
Project Description
Mutual information is an Information Theoretic quantity that describes the dependence between two random variables that cannot be captured by linear correlation. Maximizing mutual information is an approach to developing efficient experimental designs that maximize the amount of information gained from each test performed. Analytically computing mutual information is difficult and can be performed only in special cases, so we are estimating it from samples. Current mutual information estimators are not designed to accurately estimate highly dependent relations when input dimensions are larger than two. Our work is to extend these estimators to higher dimensional and higher dependence situations and validating their ability to guide experimental design choices.
Project Relevance to Nuclear Nonproliferation
Using mutual information is an optimal method for the deployment of mobile radiation sensor network. Maximizing mutual information indicates the location where new sensor readings are most informative for localizing a rogue nuclear material. Utilizing an intelligent sensor strategy will minimize the time to capture the material.
University: North Carolina State University
Advisor: Eric Laber and Ralph Smith
Lab Mentor: Brian Weaver and Brian Williams
Computer, Computational, and Statistical Sciences Division
Statistical Sciences Group (CCS-6), LANL
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Products and Outcomes of Project
Our improved mutual information that utilizes ideas from manifold learning that is capable of estimating mutual information between highly dependent random variables up to 50 dimensions. This work will directly impact CNEC research on mobile sensor placement in the coming year.
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Ryan O’Mara
Project Title
New Methods for Solving Inverse Transport Problems
Project Objective
Test the utility of two new methods for solving inverse transport problems.
Project Description
Inverse radiation transport problems are a broad set of problems that involve determining unknown quantities from radiation measurements, i.e. gamma ray spectra. Problems within this class are often characterized by noisy solution spaces and black-box objective functions. Prior studies have shown that when the derivatives of a measured quantity with respect to the unknown quantity are available, gradient based optimization routines can quickly identify solutions. However, for many problems derivative information for measured quantities is unavailable.
The aim of this project is to test the ability of two non-gradient based methods to solve inverse radiation transport problems. Gnowee is a metaheuristic optimization routine that was designed to find near-globally optimal solutions to black-box optimization problems. The delayed rejection adaptive metropolis (DRAM) routine is an implementation of Markov chain Monte Carlo methods for determining the expected values of a set of unknowns, with their associated distributions.
In order to test these two approaches, each was used to solve a number of photon and neutron problems. In each test case, “measured” quantities (i.e. uncollided photon leakage, neutron leakage, etc.) were calculated using transport codes. Then the optimization routines were used to estimate unknown source characteristics.
University: North Carolina State University
Advisor: Dr. Robert Hayes
Lab Mentor: Dr. Jeff Favorite
X Computational Physics Division
Monte Carlo Methods, Codes and Applications, LANL
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Project Relevance to Nuclear Nonproliferation
Radiation measurements are the primary instrument available in the verification and nuclear nonproliferation spaces. The goal of such measurements is to maximize the amount of information obtained from the acquired data. The optimization methods tested could be implemented into future methods for acquiring information about source material characteristics from radiation measurements.
Products and Outcomes of Project
The above optimization routines were shown to be promising methods for extracting important information from routine radiation measurements. In addition, an interface was written to communicate between these routines and three transport codes (MCNP, SENSMG and SENSPG), which will allow for further testing of the capabilities of these routines.
Publications and Reports
• R.P. O’MARA and J. A. FAVORITE, “Non-Gradient Based Optimization Methods for Blackbox Inverse Transport Problems,” Los Alamos National Laboratory, LA–UR–18–????? (August, 2018).
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Simone Santos
Project Title
Algorithms for ubiquitous networks of sensors
Project Objective
Store GPS locations of known locations with expected sources to be found near given locations and determine when a static/mobile source is potentially present.
Project Description
We used DES®Kromek CsI sensors and 3x3 NaI sensors to collect sensor and source data. We then extracted known locations of medical centers and hospitals to update algorithms to include these locations as we expect to find x-rays and medical isotopes near these locations. We then used a distance factor and determined an increased opportunity of finding given isotopes near these locations. We then implemented a slight bias to help our identification method to properly identify a given signal. With determining whether a potential source is static/mobile we used the GPS time and locations to distinguish the two. For static source we determined that only when a detector is in motion is when a static source can present itself, and mobile sources are always potentially present both when the detector is in motion and when the detector itself is static.
Project Relevance to Nuclear Nonproliferation
This project is of paramount importance to the Nuclear Nonproliferation community. Equipping security personnel with these devices can greatly enhance and expedite the detection and localization of radioactive materials. By including machine learning to the known locations of static sources through multiple passes of these detectors and included known biased locations for given isotopes; we can better equip the algorithm to properly identify whether there are radioisotopes present.
University: University of North Carolina A&T
Advisor: Abdellah Ahmidouch
Lab Mentor: Simon Labov
Global Security Principal Directorate
Physics and Life Sciences Group, LLNL
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Products and Outcomes of Project
Although this project is ongoing, we have continued to provide substantial support to the team and the program. We have started to produce detailed analysis of updated locations of known sources and updating the system to determine when the detector is static to update our background data for given locations.
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Aric Tate
Project Title
Relative Efficiency Test of Carbon Fiber Drift Tubes
Project Objective
Determine plausibility of using slowly leaking lightweight detector modules for imaging of structural support inside of cathedral dome.
Project Description
The P-25 Threat Reduction Team at LANL have developed lightweight carbon fiber drift tubes to be used to scan the dome of Brunelleschi in Florence, Italy. Muon scattering radiography, developed at LANL, uses cosmic-ray muons to image dense or shielded objects by determining how much each muon scatters as it passes through a given volume. In order to properly image the dome, the detector must take data for an extended period of time. Previous drift tube designs were constructed of individually sealed aluminum tubes. The weight of this aluminum version of drift tube modules exceeded the allowed weight that the dome could safely support. The new modules consist of hollow carbon fiber cylinders glued to 3D printed conducting plastic manifolds. Although much lighter, some of these detectors exhibit slow leaks, as they are not individually sealed like their aluminum counterparts. The pressure of the carbon fiber modules can be kept relatively constant by attaching the modules to a pressure regulator allowing only a small amount of air to gradually enter to detector. If the efficiency of a slowly leaking module is able to remain at an acceptable rate, no additional detectors need to be constructed.
Project Relevance to Nuclear Nonproliferation
Muon scattering radiography was developed as a nonproliferation technique specifically intended for the scanning of cargo containers to detect high Z materials. This imaging technique has evolved to include treaty verification capabilities such as the imaging of fuel rods stored in
University of Illinois Urbana-Champaign
Advisor: Kathryn Huff
Lab Mentor: Elena Guardincerri
P-25 Threat Reduction Group, LANL
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dry casks. By demonstrating the effectiveness of muon radiography, we hoped to expand its use in both nonproliferation structural applications.
Products and Outcomes of Project
The efficiency test is ongoing, as is the construction of the lightweight aluminum frame.
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Kenneth Tran
Project Title
X-Net: Bimodal Feature Representation Learning in Satellite Imagery
Project Objective
Our aim is to learn a joint representation between multispectral and visible color remote sensing data using deep learning.
Project Description
In September 2017, IARPA released challenge problem with a novel data set, called the Functional Map of the World (fMoW) that contains the largest amount of labelled remote sensing data. For the labels, fMoW provides at least one bounding box per image and the class that image patch belongs to. In total, there are 63 categories, including military facility and nuclear power plant. Given a satellite image and the bounding boxes, the goal of the competition is to classify individual image patches. One property of fMoW is that two images of the same region are captured simultaneously, one being visible color imagery (3 bands) and the other being multispectral imagery (either 4 or 8 bands). This makes the data multimodal in the sense that there are two unique image inputs with varying channel numbers and spatial resolutions. In the final results of the competition, the top three contestants only used the visible color imagery. In our work, we are interested in combining these two modalities in a meaningful way to enhance classification performance. We believe that by finding a meaningful joint representation between the two modalities, we can enhance the performance of the classification task.
Project Relevance to Nuclear Nonproliferation
Satellite imagery data is easy to obtain and can be used to track activities such as resource allocation and construction that are indicative of nuclear proliferation. Improving the performance of point of interest classification leads to enhanced capabilities for pattern detection when there are enough images available to analyze.
University: North Carolina State University
Advisor: Hamid Krim
Lab Mentor: Wesam Sakla
Computer Engineering Division
Computer Vision Group, LLNL
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Products and Outcomes of Project
We designed a novel bimodal autoencoder architecture for remote sensing data that is inspired by previously successful architectures for image segmentation and classification. A byproduct of our network is learning an encoder which is trained without labels (unsupervised learning) and can be used as a feature extractor between two modalities. This encoder can then be transferred to supervised tasks, such as classification or detection.
Presentations
• (Poster) K. TRAN and W. SAKLA, “X-Net: Bimodal Feature Representation Learning in Satellite Imagery,” Data Science Workshop, Livermore, California, August 7-8, 2018, LLNL Data Science Institute (2018).
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Sophie Weidenbenner
Project Title
Significant Second-Order Sensitivity Analysis Contributions to Radiation Detector Responses
Project Objective
Conceive a benchmark problem to demonstrate the importance of using higher order sensitivities for unscattered gamma rays and neutrons.
Project Description
The goal of this project is to determine when second-order uncertainty analysis produces meaningfully different results from a first-order analysis. With SENSPG and the MCNP PERT card, second-order sensitivities can now be computed, allowing us to do second-order uncertainty analysis. For this analysis, knowledge of the second-order sensitivities are required to compute the skewness of a response. The events occurring in the skewed tails of a response, which are characteristic of events such as major accidents or catastrophes, could likely be missed if the second-order sensitivities were ignored. However, calculations such as these are rarely ever done.
The methodology of this project involves the use of the Second-Order Adjoint Sensitivity Analysis Methodology (2nd-ASAM) developed by Cacuci to compute the first- and second-order sensitivities of a detector’s response with respect to the system’s isotopic number densities, microscopic cross sections, and source emission rates. The multigroup discrete ordinates code PARTISN was used to solve the equations involved in the 2nd-ASAM. Using the first- and second-order sensitivities along with various assumed relative standard deviations, the contribution of the second-order sensitivities to the expected value and the variance of a response was computed along with the skewness of a response.
University: Purdue University
Advisor: Miltos Alamaniotis
Lab Mentor: Jeff Favorite
X Division
Monte Carlo Methods, Codes, and Applications Group, LANL
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Project Relevance to Nuclear Nonproliferation
Understanding uncertainties is an essential part of the computational and theoretical work we are doing to support nuclear nonproliferation missions. We are seeking to understand when the standard first-order uncertainty analysis, applied ubiquitously, is inadequate.
Products and Outcomes of Project
PYTHON was used to develop a code to generate and run input files for SENSPG and then perform the necessary second-order analysis calculations using the data generated in the SENSPG output files. Several cases were run showing instances where second-order uncertainty analysis produces meaningfully different results from a first-order sensitivity analysis. We hope to generalize these cases to show definitively when second-order analysis is significant.
Publications and Reports
• S. L. Weidenbenner, “Significant Second-Order Sensitivity Analysis Contributions to Radiation Detector Responses,” Los Alamos National Laboratory, LA–UR–17–????? (August, 2018).
SECTION IV: FELLOWS 2018
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Jennifer Arthur
Project Title
Subcritical Neutron Multiplication Inference Measurements for Nuclear Data and Computational Methods Validation
Project Objective
Perform subcritical neutron multiplication inference measurements, compare measured and simulated results, and influence future nuclear data evaluations and computational methods development.
Project Description
LANL has performed many subcritical benchmark measurements with bare and reflected BeRP ball configurations. Measurements on more complex systems, such as research reactors, are the next step in subcritical neutron multiplication experiments. Correlated neutron data from the measurements are used to validate Monte Carlo (MC) predictive simulation capabilities. This comparison between simulated and measured data is also used to develop a toolkit for influencing future nuclear data evaluations. The Critical and Subcritical 0-Power Experiment at Rensselaer (CaSPER) and the Subcritical Copper-Reflected α-Phase Plutonium (SCRαP) measurement were completed in July and December of 2016, respectively.
Project Relevance to Nuclear Nonproliferation
MC simulations of special nuclear material (SNM) are extensively used in the field of nuclear nonproliferation for applications such as SNM identification and characterization, experiment planning, and detection system development. Both reliable MC simulation codes and accurate nuclear data knowledge are necessary in order to precisely predict the results of SNM measurements.
University: University of Michigan
Advisor: Sara Pozzi
Lab Mentor: Rian Bahran, Jesson Hutchinson
Critical and Subcritical Measurements Team
Advanced Nuclear Technology (NEN-2) Group, LANL
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Products and Outcomes of Project
The current outcomes of this project include the publication of multiple journal papers. The first describes the development of a research reactor protocol for neutron multiplication measurements similar to the CaSPER measurement. The second documents a validation of the performance of correlated fission multiplicity implementation in several different radiation transport codes using subcritical neutron multiplication benchmark experiments. A detailed benchmark model of the SCRαP measurement has been created, and the completed benchmark evaluation will be submitted to the ICSBEP handbook. Progress is being made towards a journal paper describing a genetic algorithm that is being developed for nuclear data evaluation.
Publications and Reports
• J. ARTHUR, R. BAHRAN, J. HUTCHINSON, et al., “Validating the performance ofcorrelated fission multiplicity implementation in radiation transport codes withsubcritical neutron multiplication benchmark experiments,” Annals of Nuclear Energy,120 (2018), pp. 348-366.
• J. ARTHUR, R. BAHRAN, J. HUTCHINSON, et al., “Development of a research reactorprotocol for neutron multiplication measurements,” Progress in Nuclear Energy, 106(2018), pp. 120-139.
• J. ARTHUR, R. BAHRAN, J. HUTCHINSON, et al., “Improved Figure of Merit for FeynmanHistograms,” ANS Winter Meeting and Nuclear Technology Expo, Washington, D.C., Oct.29 – Nov. 2, 2017, LA-UR-17-24790.
• R. BAHRAN, J. HUTCHINSON, J. ARTHUR, et al., “Development of a Research ReactorProtocol for Neutron Multiplication Measurements,” ANS Winter Meeting and NuclearTechnology Expo, Las Vegas, NV, Nov. 6-10, 2016, LA-UR-16-24665.
• J. ARTHUR, R. BAHRAN, J. HUTCHINSON, et al., “Comparison of the Performance ofVarious Correlated Fission Multiplicity Monte Carlo Codes,” ANS Winter Meeting andNuclear Technology Expo, Las Vegas, NV, Nov. 6-10, 2016, LA-UR-16-24512.
• J. ARTHUR, R. BAHRAN, J. HUTCHINSON,” Analysis of the July 2016 Critical and Sub-critical 0-Power Experiment at Rensselaer (CaSPER) Measurement Campaign,” MemoNEN-2: 17-001, LA-UR-17-20881 (Jan. 20, 2017).
• J. HUTCHINSON, R. BAHRAN, T. CUTLER, et al., “Subcritical Copper-Reflected α-phasePlutonium (SCRαP) Measurements and Simulations,” International Conference onMathematics and Computational Methods Applied to Nuclear Science and Eng, Jeju,South Korea, April 16-20, 2017, LA-UR-17-20621.
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Connor Awe
Project Title
A Time Projection Chamber for Reactor Monitoring.
Project Objective
I am attempting to construct a neutrino detector capable of kinematically reconstructing a neutrino’s momentum via inverse beta decay on hydrogen. I am considering several detector concepts to accomplish this, the primary one being a time projection chamber filled with isobutane or n-pentane.
Project Description
Neutrinos have long been considered a powerful tool for exploring physics beyond the standard model and have been recognized as having applications in nuclear reactor monitoring and non-proliferation efforts. In particular, there is interest on the part of both the physics and nuclear security communities in a discrete neutrino detector; however, the experimental difficulties associated with detecting neutrinos in a high background environment have hampered past efforts, forcing experiments underground. I am working on a plan to construct a compact optical time projection chamber (TPC) capable of the kinematic reconstruction of an inverse beta decay event in hydrogenated material at a reactor. Because of the resulting directional capability, the detector may meet the needs of the nuclear security community and provide a mechanism to reduce backgrounds in fundamental neutrino physics searches. A parallel detection channel may also provide a good probe of the neutrino magnetic moment. A working low background detector would additionally be of interest to future light WIMP searches, where coherent elastic neutrino - nucleus scattering from solar neutrinos will soon be an irreducible background.
Project Relevance to Nuclear Nonproliferation
Neutrinos have long been proposed as a tool for reactor monitoring as part of a non-proliferation program because they are copiously produced by the fission process and cannot be
University: Duke University
Advisor: Phil Barbeau
Lab Mentor: Jason Newby
Nuclear Security and Isotope Technology Division, ORNL
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shielded. The biggest obstacle to this at present is the relatively high backgrounds introduced by ambient radiation and neutrinos from other sources. The ability to kinematically reconstruct, and thereby point back to, a neutrino source is of great potential interest as a means of reducing experimental backgrounds at a reactor. Such a detector may also be useful in identifying covert radiological activity.
Products and Outcomes of Project
Neutron beam experiments at the triangle universities nuclear laboratory’s tandem Van de Graff accelerator have confirmed our ability to detect low energy neutron recoils on hydrogen in the form of liquid scintillator. Existing data and simulations suggest that detection ionization signals in gaseous hydrocarbons (isobutane, n-pentane, etc.) should therefore be possible. We are working to demonstrate this with an isobutane wire chamber.
Parallel work is ongoing to design and build a time projection chamber. An inverse beta decay event generator has been written with which we are exploring different detection schemes and ways of identifying new physics.
Publications and Reports
• https://arxiv.org/abs/1804.06457 - Also submitted to Phys. Rev. C, where it is under review.
• https://www.dropbox.com/s/u6zmnn02ryjjywb/CAwe_Prelim_Report.pdf?dl=0 – Prelim report outlining my project. This was submitted to Duke and approved in spring 2018.
Presentations
• “From CEvNS to Reactor Monitoring” – 10 minute talk at the CNEC AB Board meeting in Raleigh, NC. Feb. 8th, 2018
Figure 3 – Nuclear quenching factors for EJ301 liquid scintillator. The results of my analysis are shown in red. A parallel analysis of the same data is in blue, and values from a previous experiment with plastic scintillator are in green.
Investigation of Detectors, Algorithms, and Systems for Wearable Intelligent Nuclear Detection (IDEAS for WIND).
Project Description
This year was focused on building a backpack detector array prototype to quickly detect and locate non-natural radiation sources in an urban environment. The previous year was spent on simulating designs for this prototype. The final design currently being debugged includes 3 scintillators, 2 Sodium Iodides and 1 CLYC, placed within a fixed geometry inside a robust carbon fiber chassis. The chassis is to house not only the detectors, but the GPS sensor, battery, digitizer and laptop. There is also a focus in integrating this system within the WIND program’s modular architecture. The program’s goal is to have multiple hardware and software vendors, from both national laboratories and industry, to agree upon a set standard such that any developed algorithm or monitoring system can immediately interact with any of created measurement systems. A subset of definitions include the measurement system’s capability and sensitivity to detect different types of radiation, accuracy in location estimates, and contextual sensor configurations.
In collaboration with the University of Tennessee’s Electrical and Computer Eng Department, promising approaches in both fusing real time direction estimates with video object detection and tracking have been investigated. Measurements are in progress to demonstrate the capability of using video data to aid the localization and tagging of moving sources. The future focus of the project is to understand the current capability of localizing moving radiation sources in an urban environment using solely radiation and GPS data, in order to quantify the inclusion of video or LIDAR information.
University: University of Tennessee - Knoxville
Advisor: Jason Hayward
Lab Mentor: Dan Archer
Nuclear Security and Isotope Technology Division
Nuclear Security Modeling Group, ORNL
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Project Relevance to Nuclear Nonproliferation
Designing a portable backpack system to access challenging environments, such as a sports stadiums or the cargo hold of a ship, in order to detect and locate radioactive material used for malicious intent. With this system, investigation of localization capability of both static and mobile radiation sources can be quantified. Furthermore, quantifying the performance gain due to inclusion of different data modalities can be performed.
Products and Outcomes of Project
Simulated and characterized a number of detector arrays. Built backpack radiation detector array prototype. Implemented Video Object Detection and Tracking.
Publications and Reports
• B. AYAZ-MAIERHAFER, C.G. BRITT, A.J. AUGUST, H. QI, C.E. SEIFERT, J.P. HAYWARD, “Design optimization for a wearable, gamma-ray and neutron sensitive, detector array with directionality estimation,” Nuclear Inst. and Methods in Physics Research, A (2017), http://dx.doi.org/10.1016/j.nima.2017.07.020
Presentations
• C. BRITT, B. AYAZ-MAIERHAFER, A. AUGUST, E. GREENLEE, C. E. SEIFERT, H. QI, J. P. HAYWARD, “Trade-Off Analysis for Radiation Detector Array Configurations,” Defense Nuclear Nonproliferation Research and Development University Program Review 2017, Walnut Creek, CA, June 6-8, 2017.
• C. BRITT, B. AYAZ-MAIERHAFER, A. AUGUST, E. GREENLEE, C. E. SEIFERT, H. QI, J. P. HAYWARD, “Trade-Off Analysis for Radiation Detector Array Configurations,” Nuclear Science Symposium and Medical Imaging Conference, Atlanta, GA, October 21-28, 2017. IEEE NPSS (2017).
• B. AYAZ-MAIERHAFER, C.G. BRITT, A.J. AUGUST, H. QI, C.E. SEIFERT, J.P. HAYWARD, “Design optimization for a wearable, gamma-ray and neutron sensitive, detector array with directionality estimation,” Nuclear Science Symposium and Medical Imaging Conference, Atlanta, GA, October 21-28, 2017. IEEE NPSS (2017).
• C. BRITT, H. QI, J. P. HAYWARD, “Radiation Detection using Convolutional Neural Networks,” Consortium for Nonproliferation Enabling Capabilities Workshop, Raleigh, NC, February 8-9, 2018.
• C. BRITT, H. QI, J. P. HAYWARD, “Radiation Detection using Convolutional Neural Networks,” Defense Nuclear Nonproliferation Research and Development University Program Review 2018, Ann Arbor, MI, June 5-7, 2018.
• C. BRITT, H. QI, J. P. HAYWARD, “Radiation Detection using Convolutional Neural Networks,” Symposium on Radiation Measurements and Applications, Ann Arbor, MI, June 11-14, 2018.
Project Title Data assimilation of nuclear cross sections applied to neutron multiplicity counting experiments.
Project Objective To use perturbation theory-based sensitivity analysis (SA) and uncertainty quantification (UQ) applied to neutron multiplicity counting (NMC) experiments to inform adjustments to the nuclear cross section via parameter estimation.
Project Description Nuclear cross section evaluations are currently performed using keff eigenvalue and reaction rate experiments [1], but this has resulted in biases in expected values of some nuclear parameters, such as Pu-239 nu-bar [2]. NMC experiments are a method of non-destructive assay (NDA) of special nuclear material (SNM) [3]. Each NMC distribution moment is a function of the cross sections raised to a power denoted by that moment [4]; consequently, calculations of higher-order multiplicity moments are more sensitive to the changes in the nuclear parameters than the mean, which is equivalent to gross counting. Performing data assimilation (DA) using higher-order moments of the NMC distribution would therefore lead to more precise estimates of cross sections values and their uncertainty.
The SA methodology developed by O'Brien [4] allows us to perform the DA utilizing the second and higher-order NMC moments, whereas previous DA efforts [2], [5] using keff eigenvalue and reaction rate experiments were limited to use of the mean count rate only.
Project Relevance to Nuclear Nonproliferation Miller et al [2] demonstrated that simulations of NMC experiments with a 4.5 kg sphere of weapons-grade plutonium metal, a.k.a. the BeRP ball [6], consistently over predict the measured NMC distribution mean and variance. Inverse analysis methods that utilize the NMC distribution, such as the Feynman variance-to-mean technique [7], would therefore provide inaccurate estimates of source properties (e.g. neutron multiplication). A small (~1%) decrease in the nominal ENDF-B/VII Pu-239 𝜈𝜈 value resulted in better agreement between simulated and measured NMC distributions. Our DA methodology will provide a more rigorous method for providing more accurate and precise cross sections.
University: North Carolina State University
Advisor: John Mattingly
Lab Mentor: Jeff Favorite
Computational Physics Division
Monte Carlo Methods, Codes, and Applications Group, LANL
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Products and Outcomes of Project We have used PARTISN [8] simulations of NMC experiments of the nPod neutron multiplicity counter counting the BeRP ball to perform SA and UQ applied to the first and second NMC distribution moments. We have observed that the second NMC distribution moment is indeed more sensitive to changes in the cross sections that the first NMC distribution moment. We have further observed that the distribution moments are the most sensitive to changes in the fast group fission parameters, i.e. nubar and the fission cross section, for the BeRP ball reflected by polyethylene. The next step is to implement parameter estimation that is informed by the SA and UQ steps to produce more accurate and precise cross sections.
Publications and Reports • CLARK and J. MATTINGLY, "Data Assimilation of Nuclear Cross Sections applied to Neutron
Multiplicity Counting Experiments ", Proceedings of the 2018 American Nuclear Society Annual Meeting, Philadelphia, Pennsylvania, June 2018. Invited paper.
• CLARK and J. MATTINGLY, "Data Assimilation of Nuclear Cross Sections applied to Neutron Multiplicity Counting Experiments", CNEC Workshop 2018, Raleigh, North Carolina, February 2018. Presentation.
• CLARK, M. SMITH-NELSON, and J. HUTCHINSON, “Using MCNP6 to Estimate Fission Neutron Properties of a Reflected Plutonium Sphere,” Los Alamos National Laboratory, LA-UR-17-27089, August 2017.
References • D. L. SMITH, “Evaluated nuclear data covariances: The journey from endf/b-vii.0 to endf/bvii.1,"
Nuclear Data Sheets, vol. 112, pp. 3037-3053, 2011. https://doi.org/10.1016/j.nds.2011.11.004. • E. C. MILLER, et al., “Computational evaluation of neutron multiplicity measurements of
polyethylene reflected plutonium metal," Nucl. Sci. and Eng., vol. 176, pp. 167-185, 2014. http://dx.doi.org/10.13182/NSE12-53.
• M. SMITH-NELSON, et al., “Neutron Specialist Handbook and Informational Text,” LA-UR-07-6170 (2007).
• S. E. O’BRIEN, J. MATTINGLY, and D. ANISTRATOV, “Sensitivity Analysis of Neutron Multiplicity Counting Statistics for a Subcritical Plutonium Metal Benchmark using First-Order Perturbation Theory,” Nuc. Sci. and Eng., Vol. 185, No. 3, pp. 406-425, March 2017, https://doi.org/10.1080/00295639.2016.1272988
• R. T. EVANS, J. K. MATTINGLY, and D. G. CACUCI, “Sensitivity analysis and data assimilation in a subcritical plutonium metal benchmark," Nucl. Sci. and Eng., vol. 176, pp. 325-338, 2014. Doi: http://dx.doi.org/10.13182/NSE13-24.
• J. MATTINGLY, “Polyethylene-reflected plutonium metal sphere: Subcritical neutron and gamma measurements," SAND2009-5804, Sandia National Laboratory, 2009, https://doi.org/10.2172/974870.
• J. MATTINGLY, “Computation of Neutron Multiplicity Statistics using Deterministic Transport,” IEEE T. Nucl. Sci., 59, 2, 314–322 (April 2012), https://doi.org/10.1109/NSSMIC.2009.5402335.
• R. E. Alcouffe, et al., “PARTISN: Time-Dependent, Parallel Neutral Particle Transport Code System,” Los Alamos National Laboratory, Nov. 2008.
Project Title Verification of a Conservative Transuranic Activity Assay Method in Air Samples
Project Objective Introduce transuranic isotopes to air sample counting environment for verification of rapid, conservative activity assay method.
Project Description Air sampling in radiological emergency response scenarios is complicated by overlapping energy spectra of naturally occurring radon progeny with the transuranic isotopes of interest to public health. The method has been previously tested for samples not expected to contain statistically significant transuranic (TRU) activity above background. For validation testing, Pu-239 alpha emitting, and Th-230 alpha/beta emitting check sources were used to simulate TRU content from a filter into the counting environment. Background studies of the source and blank filters (void of natural radon progeny interferences) provided characterization for comparison against filters collected with natural radon progeny present. Using Levenberg-Marquardt (LM) fitting to a time-series activity decay curve, a TRU (long-lived) activity estimate is determined. As consequence of the LM fitting, uncertainty estimators are also possible due to the errors in the reported fit parameters. Utilizing the validation of the method for scenarios with both TRU and no TRU activity present, an operational procedure is being developed to allow for flexibility in the counting equipment to acquire time-series decay measurements and to automate scripting of the post-processing analysis. With an automated script, work package documentation and procedure, this method will contribute to the capabilities for radiological emergency response.
Project Relevance to Nuclear Nonproliferation In radiological emergency response, estimates of transuranic activity are confounded by natural radon progeny in the air. Radiochemical filter analysis is available on the order of weeks, leaving an information gap crucial in emergency response decision making. This assay method provides a technical basis for informed protective action decisions within hours.
Products and Outcomes of Project Measurements and analysis of the assay method provided conservative transuranic activity estimates within hours for various Pu-239 and Th-230 sources. Use of the Th-230 data allows for expansion of the method to include both alpha and beta
University: North Carolina State University
Advisor: Robert Hayes
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activity estimates. The method seeks to reduce estimation complexity and will provide the radiological emergency response community with an operational procedure for potential implementation in response frameworks.
for Mixed Alpha/Beta Air Samples,” American Nuclear Society Winter Meeting, (2018). • S.J. COPE, R.B. HAYES. (accepted). “Incremental Gains of a Conservative Transuranic Alpha
Activity Assay Method in Air Samples,” American Nuclear Society Advances in Nuclear Nonproliferation Technology and Policy Conference (ANTPC), (2018).
• S.J. COPE, R.B. HAYES. “Preliminary work toward a Transuranic Activity Estimation Method for Rapid Discrimination of Anthropogenic from Transuranic in Alpha Air Samples.” Health Phys 114-3:319-327; 2018, https://news.ncsu.edu/2018/02/airborne-radiological-detection-2018/
• S.J. COPE, R.B. HAYES. “Mass Correlation of Presumed Twin Air Filters for Emergency Response Applications,” Transactions of the American Nuclear Society, Vol. 117:1159-1161 (2017).
Presentations • SJ. COPE, RB. HAYES. “Validation of a rapid, conservative transuranic alpha activity estimation
method in air samples”. 63rd Annual Health Physics Society Meeting. Cleveland, OH, July 9-13, 2018.
• SJ. COPE, RB. HAYES. “A rapid, conservative TRU alpha activity estimation method in air monitoring for radiological emergency response”. NNSA University Program Review (UPR) Meeting. Ann Arbor, MI, June 5-7, 2018.
• SJ. COPE, RB. HAYES. “Validation Tests of a Rapid TRU Estimation Method in Air Sampling”, 22nd Annual Technical Seminar of the Savannah River Chapter Health Physics Society. Aiken, SC, April 27, 2018.
• SJ. COPE, RB. HAYES. “Gross Alpha Analysis for Radiological Emergency Response Air Sampling”, North Carolina Health Physics Society Spring Meeting. Raleigh, NC, March 2, 2018.
• SJ. COPE, RB. HAYES. “A rapid, conservative TRU alpha activity estimation method in air monitoring for radiological emergency response and remote radioaerosol assay”, CNEC Annual Workshop and Advisory Board Meeting. Raleigh, NC, February 8-9, 2018.
• SJ. COPE, RB. HAYES. “Twin Air Filters and Seasonal Comparison of NORM Concentrations”, 29th Annual Air Monitoring Users Group (AMUG) Meeting. Las Vegas, NV, November 13-14, 2017.
• SJ. COPE, RB. HAYES. “Review of Fixed-Filter CPAM Integrated-Counts Processing Analysis”, 29th Annual Air Monitoring Users Group (AMUG) Meeting. Las Vegas, NV, November 13-14, 2017.
• SJ. COPE, RB. HAYES. “NORM Air Sampling and Analysis for Radiological Emergency Response”. Sigma Xi Symposium on Atmospheric Chemistry, Climate, and Health. Raleigh, NC, November 10-11, 2017.
• SJ. COPE, RB. HAYES. “Mass Correlation of Presumed Twin Air Filters for Emergency Response Applications”, ANS Winter Meeting. Washington DC, October 29-November 2, 2017.
• SJ. COPE, RB. HAYES. “Transuranic Air Filter Analysis Techniques”, INMM Novel Technologies, Techniques and Methods for Safeguards and Arms Control Verification. Albuquerque, NM, August 29-30, 2017.
Developing Machine Learning Prediction Capabilities of Uranium Enrichment Based on Gamma-Gamma Coincidence Signatures
Project Objective
Develop algorithms which identify trends in gamma-gamma coincidence datasets of uranium with invariance across multivariate parameters.
Project Description
The primary difficulty of obtaining useful information from gamma-gamma coincidence spectra is the process of determining which spectral features are useful for drawing a conclusion. This is especially true for dense and complicated coincidence spectra, such as those of fission products from irradiated uranium samples. A set of binary classification support vector machine algorithms was trained with supervised learning on gamma-gamma coincidence data from irradiated uranium samples of natural, low, and high-enriched uranium. The resulting model will be capable of classifying uranium samples into the correct enrichment regime (natural, low, or high) based on their gamma-gamma coincidence spectra. Current results with the binary classification support vector machines indicate a 92% classification accuracy. This eliminates the need for a spectral analyst to parse through the data and manually determine which spectral features are indicative of enrichment. The basic functions used by the model to make classification decisions can also inform the analyst of less obvious spectral features that are highly indicative of enrichment. There exists ongoing work to improve classification accuracy and basis function identification.
University: University of Texas at Austin
Advisor: Sheldon Landsberger
Lab Mentor: Ken Dayman
Nuclear Security and Isotope Technology Division
Nuclear Security Modeling Group, ORNL
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Project Relevance to Nuclear Nonproliferation
This project advances nuclear nonproliferation by adding to the toolbox available to nuclear forensics researchers when studying intercepted nuclear materials. Furthermore, identifying new features of fission product coincidence data that strongly correlate with uranium enrichment levels adds to the fundamental knowledge of fission product yields which will aid further efforts to develop means of enrichment determination.
Products and Outcomes of Project
Support vector machine learning prediction models have been created which are capable of classifying uranium enrichment into one of three regimes (natural, low, or high) with 92% accuracy. Further work will consider alternate learning methods such as neural networks, and will refine the resolution of the predictions to provide regression models which predict enrichment to within a tolerated percentage.
Publications and Reports • ADAM DRESCHER, SHELDON LANDSBERGER, DEREK HAAS, “Developing Support
Vector Machine Prediction Capabilities of Uranium Enrichment Based on Gamma-Gamma Coincidence Signatures”, IEEE 2017 Nuclear Science Symposium and Medical Imaging Conference Proceedings, Atlanta, GA, Oct 21–28, 2017.
• ADAM DRESCHER, BRANDON DE LUNA, MARJOLEIN PASMAN, DEREK HAAS, SHELDON LANDSBERGER, “Revamping of a Graduate Radiochemistry Course for Nuclear Forensics Applications”, Proceedings of the 26th International Conference on Nuclear Eng, London, England, Jul 22-26, 2018.
• ADAM DRESCHER, MICHAEL YOHO, SHELDON LANDSBERGER, “Gamma-Gamma Coincidence in Neutron Activation Analysis”, Journal of Radioanalytical and Nuclear Chemistry, 2018. DOI: 10.1007/s10967-018-6033-8
Presentations • ADAM DRESCHER, SHELDON LANDSBERGER, DEREK HAAS, “Developing Analytical
Techniques for Nuclear Safeguards Assay with Coincidence LaBr3:Ce Gamma-Ray Spectrometry”, IEEE 2017 Nuclear Science Symposium and Medical Imaging Conference, Atlanta, GA, Oct 21-28, 2017.
• ADAM DRESCHER, KEN DAYMAN, DEREK HAAS, SHELDON LANDSBERGER, “Developing Prediction Capabilities of Uranium Enrichment Based on Gamma-Gamma Coincidence” 2018 CNEC Workshop Advisory Board Meeting, Raleigh, NC, Feb 8-9, 2018.
• ADAM DRESCHER, BRANDON DE LUNA, MARJOLEIN PASMAN, DEREK HAAS, SHELDON LANDSBERGER, “Revamping of a Graduate Radiochemistry Course for Nuclear Forensics Applications”, Proceedings of the 26th International Conference on Nuclear Eng, London, England, Jul 22-26, 2018.
• ADAM DRESCHER, MICHAEL YOHO, SHELDON LANDSBERGER, “Gamma-Gamma Coincidence in Neutron Activation Analysis”, Methods and Applications of Radiochemistry XI, Kailua-Kona, Hawaii, Apr 8-13, 2018.
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Samuel Hedges
Project Title
Observing low-energy neutrino interactions in a NaI[Tl] detector at the SNS
Project Objective
Develop and deploy a NaI[Tl] detector to observe coherent elastic neutrino-nucleus scattering (CEvNS) and charged-current neutrino interactions at the Spallation Neutron Source.
Project Description
The COHERENT collaboration recently made the first successful detection of coherent elastic neutrino-nucleus scattering (CEvNS) at the SNS. CEvNS is a standard model process in which a low energy neutrino interacts coherently with the nucleons inside a nucleus, leading to a large cross section enhancement. This has generated interest as a means to non-intrusively measure reactor neutrinos to study characteristics of reactor cores. Additionally, CEvNS is important for understanding supernova dynamics, characterizing backgrounds for dark matter WIMP searches, and can be used as a test of the standard model.
COHERENT is deploying a variety of targets to test the predicted N2 scaling of the cross section with the number of neutrons in the target nucleus. The lightest of COHERENT’s target nuclei is sodium. While sodium will have a smaller cross section than COHERENT’s other targets, its nuclear recoils produced through CEvNS interactions will be more energetic. COHERENT is deploying a multi-ton NaI[Tl] detector to the SNS to study this process. For this deployment, backgrounds in the NaI[Tl] crystals must be studied, simulations must be performed to determine shielding requirements, and the support structure for the detector must be designed.
Additionally, COHERENT intends to use the same detector to study charged-current interactions in 127I to measure the cross section as a function of neutrino energy. This will allow testing of nuclear models and gA quenching. COHERENT has deployed a 185 kg prototype detector to the SNS in 2016, which is making a preliminary measurement of this cross section and studying backgrounds for the larger detector.
University: Duke University
Advisor: Phil Barbeau
Lab Mentor: Jason Newby
Nuclear Security and Isotope Technology Division
Nuclear Material Detection and Characterization Group, ORNL
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Project Relevance to Nuclear Nonproliferation
Neutrinos are produced in large quantities in nuclear reactors and are impossible to shield. By studying the characteristics of these neutrinos, it is possible to non-intrusively determine information about the core, such as on/off status and fissile content. Neutrino detectors sensitive to CEvNS will allow for smaller detector footprints, and the capability of monitoring reactors from further distances.
Products and Outcomes of Project
The 185 kg prototype detector will make an initial measurement of the charged current cross section on 127I. Initial results from this detector will inform design decisions for the ton-scale detector. The larger detector will feature PMTs with a dual-output base which will allow for simultaneously measuring low energy nuclear recoils and higher energy charged-current signals. This detector will make a measurement of the CEvNS cross section on 23Na using neutrinos produced at the SNS.
Publications and Reports
• C. Awe, P. S. Barbeau, J. I. Collar, S. Hedges, L. Li, “Liquid Scintillator Response to Proton Recoils in the 10-100 keV Range,” arXiv:1804.06457 (2018)
• D. Akimov, et al., “COHERENT 2018 at the Spallation Neutron Source,” arXiv:1803.09183 (2018)
• D. Akimov, et al., “Observation of Coherent Elastic Neutrino-Nucleus Scattering,” Science, 0036-8075 (2017).
Presentations
• S. Hedges, “A 185 kg NaI[Tl] Detector for Observing the Charged-Current Neutrino Interaction on 127I,” Neutrino 2018, Heidelberg, Germany, June 4-9, 2018
• S. Hedges, “The COHERENT Collaboration: Initial Results and Present Status,” Imperial College HEP Seminar, London, United Kingdom, May 30, 2018
• S. Hedges, “Charged Current Interactions at the SNS,” NuEclipse 2017, Knoxville, Tennessee, August 20 and 22, 2017
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Dylan Hoagland
Project Title
Adjoint Transport Discrete Response Function Simulation for Passive Gamma Emission Tomography (PGET)
Project Objective
Use deterministic adjoint gamma ray transport simulations to study transport phenomenon in a PGET collimator.
Project Description
PGET is a technology that utilizes two banks of highly collimated detectors, rotated around a spent fuel assembly, to produce a cross-sectional image of gamma radiation emissions. The imagining methodology requires an accurate transport solution to determine the detector responses when the device is place around a fuel assembly. This presents a modeling challenge, as the problem is very costly to simulate using stochastic transport, but suffers from reduced accuracy due to ray effects in the air slits of the collimator when using deterministic alternatives.
This project was conducted to address this problem in an effort to obtain comparable solution accuracy to stochastic methods using cheaper deterministic alternatives, as well as study the physical phenomenon that occurs within the collimator. The study of this phenomenon was used to assess the cause of the discrepancy between stochastic and deterministic solutions and to identify necessary conditions for accurate simulation of the collimator using deterministic methods.
With such conditions known, adjoint transport was used to generate a discrete response function for the collimator inlet which maps the forward transport solution from the assembly (where ray effects are not known to be problematic) to an energy dependent flux at the location of detectors.
University: NC State University
Advisor: Dr. Yousry Azmy
Lab Mentor: Dr. Erin Miller and Dr. Rick Wittman
National Security Directorate
Applied Physics Group, PNNL
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Project Relevance to Nuclear Nonproliferation
PGET is a technological advancement with the ability to obtain a pin-wise gamma emission distribution from spent nuclear fuel assemblies, whose success is contingent on the reliability of its supporting models. The PGET instrument enhances the IAEA’s tools for measurements to verify the correctness and completeness of a declaration.
Products and Outcomes of Project
We have studied the three proposed causes of the discrepancy between deterministic and stochastic transport methods: scattering between detectors, scattering within the collimator, and septal penetration. By theoretical analysis, scattering between detectors was deemed to be an extremely improbable event, and the effects of scattering within the collimator and septal penetration were studied and quantified though simulation. The collimator adjoint solution was then used as a discrete response function to efficiently determine the flux at detectors. The necessary conditions for a simulation to obtain such a solution were also determined to allow the study to be replicated of for the discrete response function to be created for different specifications.
Publications and Reports
On date of drafting (8/14/18) there are publications and reports planned but not written. The first will be an informal report to the Applied Physics Group summarizing work and including all relevant collected data. Additionally, a peer reviewed publication has been planned for submission to a conference. The conference to which it will be submitted is to be determined.
Presentations
Upon conclusion of this project, an informal presentation will be given to the Applied Physics Group and any other lab employees with interest in the work conducted.
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Joel Kulesza
Project Title
Automated Variance Reduction for Highly Angle-Dependent Calculations
Project Objective
Develop a tool to optimize Monte Carlo calculations using DXTRAN variance reduction for computational efficiency.
Project Description
The DXTRAN variance reduction technique available in the MCNP code system is useful in calculations with a low probability of particles making enough scattering collisions to be directed toward regions of interest (e.g., tally regions representing radiation detectors). These situations can be characterized as highly angle-dependent problems. DXTRAN operates by splitting collided particles, transporting a portion of the split particle to the surface of the region of interest, and continuing sampling. DXTRAN is the only variance reduction technique available in the MCNP code system that permits directly biasing direction and allowing continued sampling.
However, no rigorous study of DXTRAN’s unbiasedness and its effect on tally variance has been performed before. Moreover, there is no guidance available for a user to choose DXTRAN parameters while attempting to construct an efficient calculation. This work performs such a study of DXTRAN’s behavior. Using that information, a pre-existing computational cost-optimized radiation transport software tool is modified to deterministically predict DXTRAN tally response and variance behavior, and estimate computational time, to then iteratively optimize DXTRAN parameters that an end user can directly apply. Such work is expected to produce
MCNP and Monte Carlo N-Particle are registered trademarks owned by Los Alamos National Security, LLC, manager and operator of Los Alamos National Laboratory. Any third party use of such registered marks should be properly attributed to Los Alamos National Security, LLC, including the use of the designation as appropriate. Any questions regarding licensing, proper use, and/or proper attribution of Los Alamos National Security, LLC marks should be directed to [email protected].
University: University of Michigan
Advisor: Brian C. Kiedrowski
Lab Mentor: Clell J. (CJ) Solomon, Jr.
Computational Physics Division
Monte Carlo Methods, Codes, and Applications Group, LANL
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Monte Carlo calculations more efficient, with more reproducible variance reduction parameters, than are otherwise available.
Project Relevance to Nuclear Nonproliferation
Nuclear nonproliferation situations can often be characterized as highly angle-dependent problems. On a small scale, one can have a radioactive source in a room with a detector across the room or in an adjoining room separated from the source by a wall and potentially streaming paths. On a larger scale, urban environments provide similar shielding/streaming complications.
Products and Outcomes of Project
This work will produce a radiation transport software tool that predicts Monte Carlo tally response and variance, the expected Monte Carlo computational time, and ultimately optimized Monte Carlo variance reduction parameters for DXTRAN. This capability can then be applied to nuclear nonproliferation problems to yield more efficient solutions than was previously possible.
Publications and Reports • J. A. KULESZA, C. J. SOLOMON, and B. C. KIEDROWSKI, “Progress in Deterministically
Predicting Tally Variance with DXTRAN Regions,” in “Proceedings of Advances in Nuclear Nonproliferation Technology and Policy Conference (ANTPC2018),” American Nuclear Society, Wilmington, NC, USA; (September 23–27, 2018).
• J. A. KULESZA, M. L. FENSIN, and R. L. MARTZ, “Performance Assessment of Alternative Nested DXTRAN Treatments,” in “Proceedings of 20th Topical Meeting of the Radiation Protection and Shielding Division (RPSD2018),” American Nuclear Society, Santa Fe, NM, USA; (August 26–31, 2018).
• J. A. KULESZA, C. J. SOLOMON, and B. C. KIEDROWSKI, “A Monte Carlo Importance-splitting Analytic Benchmark,” in “Proceedings of 20th Topical Meeting of the Radiation Protection and Shielding Division (RPSD2018),” American Nuclear Society, Santa Fe, NM, USA; (August 26–31, 2018).
• J. A. KULESZA, C. J. SOLOMON, and B. C. KIEDROWSKI, “An Angular Biasing Method Using Arbitrary Convex Polyhedra for Monte Carlo Radiation Transport Calculations,” Annals of Nuclear Energy, 114, 437–450 (Apr. 2018).
Presentations • J. A. KULESZA, C. J. SOLOMON, and B. C. KIEDROWSKI, “Recent Work on DXTRAN
History-score Moment Equations,” National Nuclear Security Administration NA-22 University Program Review, Ann Arbor, MI, USA (Jun. 2018), Poster.
• J. A. KULESZA, C. J. SOLOMON, and B. C. KIEDROWSKI, “Recent Work on DXTRAN History-score Moment Equations,” Consortium for Nonproliferation Enabling Capability (CNEC) Annual Workshop, Raleigh, NC, USA (Feb. 2018), Presentation.
• J. A. KULESZA, C. J. SOLOMON, and B. C. KIEDROWSKI, “Initial Work to Deterministically Predict Tally Variance with MCNP6 DXTRAN Regions,” 25th International Conference on Transport Theory (ICTT25), Monterey, CA, USA (Oct. 2017), Presentation.
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Scott Richards
Project Title
Automated Problem-Specific Nuclide-Transition Selection for Reduced Order Modeling
Project Objective
To develop a general method for construction of problem-specific nuclide-transition libraries to facilitate source-term generation.
Project Description
A method for automated library reduction for the nuclide generation code Origen is being developed for increased computational efficiency of source-term generation. The tracked nuclides in depletion codes do not equally contribute to a problem, and therefore a subset of the total nuclides can be removed from the system with little loss of accuracy. Generalizing this reduction process requires establishing problem-specific metrics to measure individual nuclide contributions and overall library accuracy for a given problem. Using these metrics and their respective sensitivities to individual nuclide inventories, Origen’s full 2237 nuclide inventory can be reduced to approximately 400 nuclides while only affecting the metric of interest by less than 1 pcm (per cent mille or 10−5). The method for this problem-specific reduction relies on maintaining the physical meaning of the transition system to the highest degree reasonable — by maintaining the connectedness of the system and considering transition pathway as well as nuclide importance. This is accomplished through a weighting method to capture the importance of a nuclide to a transition rate, and by a subsystem determination method that determines the transition pathways of most importance.
University: University of Tennessee
Advisor: Dr. Steven Skutnik
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Project Relevance to Nuclear Nonproliferation
It is only through full integration of accurate source-term generation models that verification measurements can be accurately predicted and analyzed with codes, particularly in the case of used fuel. This method will reduce the computational cost of including high fidelity depletion in the user-level codes that are run with limited resources.
Products and Outcomes of Project
We have proven that the methods based on adjoint analysis and graph theory are viable for reduced order depletion modeling and have implemented these methods in the depletion code Origen. This method generates robust libraries that reduce runtimes by a factor more than ten; that can be more easily accommodated in large nonproliferation modeling codes.
Publications and Reports
• S. RICHARDS, S. E. SKUTNIK, “Problem-Dependent ORIGEN Library Compression to Increase Computational Efficiency”. Proc. International Conference on Mathematics and Computational Methods Applied to Nuclear Science and Eng (M&C 2017), Jeju, Korea, April 16-20, 2017, on USB (2017)
Presentations
• S. RICHARDS, S. E. SKUTNIK, “A Generalized Method for Robust, Problem-Specific Nuclide-Transition Selection for Reduced Order Modeling”. University Program Review Meeting 2018, Ann Arbor, Michigan, June 5-7, 2018, National Nuclear Security Administration
• S. RICHARDS, S. E. SKUTNIK, “Problem-Dependent ORIGEN Library Compression to Increase Computational Efficiency”. International Conference on Mathematics and Computational Methods Applied to Nuclear Science and Eng (M&C 2017), Jeju, Korea, April 16-20, 2017, American Nuclear Society (2017)
• S. RICHARDS, B.R. GROGAN, “Sensitivity Study of INDEPTH for Verification of Facility Spent Nuclear Fuel Declarations”. International High-Level Radioactive Waste Management Conference, Charlotte, North Carolina, April 9-12, 2017, American Nuclear Society (2017)
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Raffi Yessayan
Project Title Communication Latency Optimization for Massively Parallel Transport Codes on Shared HPCs
Project Objective Identify and mitigate the severe inefficiencies incurred in high-utilization HPC systems due to massively parallel communication.
Project Description Previous work with the PIDOTS massively parallel code has shown unexpected scaling behavior which has detrimentally impacted parallel efficiency. Specifically, earlier implementations of the Parallel Block Jacobi and Parallel Gauss-Seidel iterative schemes for solving the radiation transport equation exhibit an unexplainable growth in the execution time per iteration with increasing number of processors. It is generally expected that the cost of a communication operation on an HPC system is relatively constant with increasing number of participating processors and that the latency cost is negligible. However, this presumes that the system is un-congested and that the message sizes are relatively large so that the transmission time masks the latency penalty. For modern, shared HPCs, high utilization (i.e. high contention), is an everyday occurrence. Additionally, for massively parallel codes implementing spatial domain decomposition, the goal is to subdivide the workload as finely as possible. This leads to myriad communications with small data sizes and therefore relatively significant latency costs.
Previous analysis of communication models on the Falcon HPC system at INL revealed that, under user conditions, low message-size, high message-count communication algorithms are particularly vulnerable to communication latency-based efficiency loss. Discrete event simulations showed that this low-level communication effect could accumulate into order of magnitude increases in runtime at even moderate processor counts (~32K). For algorithms intended to run on HPCs using in excess of 100K processors, this efficiency loss is damaging. Algorithms must be designed to allow for massive domain decomposition while simultaneously minimizing the inefficiency consequences of the resulting communication scheme.
University: North Carolina State University
Advisor: Yousry Azmy
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Project Relevance to Nuclear Nonproliferation As deterministic transport problems have become increasingly high fidelity, the amount of computational resources required for their execution has dramatically increased. This led to the adoption of parallel and massively parallel methods. Better understanding of the increasing communication costs of these methods can drive significant efficiency gains and allow further increased fidelity. These high-efficiency, massively parallel algorithms can be leveraged to rapidly evaluate non-proliferation relevant scenarios such as city-scale source localization.
Products and Outcomes of Project
A novel communication algorithm has been developed to minimize the efficiency impact of communications in the PIDOTS transport code. By aggregating the communications of multiple solve domains, the total number of communications was drastically reduced. This dramatically lowers the relative cost of the latency phase of communication and improves both run time and parallel scaling for highly distributed cases. Testing is currently ongoing on FALCON and planned for a massively parallel machine soon.
Publications and Reports • R. YESSAYAN, “Improvements to the THOR Neutral Particle Transport Code on High-
Performance Computing Systems via Acceleration, Parallelization, and Performance Analysis,” Thesis, North Carolina State University. 2018.
• R. YESSAYAN, Y. AZMY, S. SCHUNERT, C. GARVEY, “Analysis of Communication Performance Degradation of the Radiation Transport Code PIDOTS on High-Utilization, Multi-User HPC Systems,”” PHYSOR 2018, Cancun, Mexico, April 22-26, 2018.
Presentations • R. YESSAYAN, Y. AZMY, “Communication Performance Degradation of the Radiation
Transport Code PIDOTS on Massively Parallel, High-Utilization, Multi-User HPC Systems,” UPR 2018, Ann Arbor, Michigan, June 4-8, 2018
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Performance Improvements for Highly Refined Regimes
